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Salary
≈ $151k – $294k per year (Estimated)
Location
In office (Sunnyvale)
Seniority
Senior · 5+ years exp

Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Oct 13, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
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Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

As Forward Deployed Engineer (FDE), you will be at the forefront of applying Google's cutting-edge Generative AI to solve real-world issues for our most strategic customers. You will act as a specialized software engineer embedded with key accounts, working to build, deploy, and optimize sophisticated AI agents across our Gemini Enterprise for Customer Experience suite and other emergent enterprise AI solutions.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Analyze customer industries and profiles to translate business logic into functional AI agents.
  • Identify necessary agent skills and APIs, map decision trees, and build system guardrails to ensure accurate outputs.
  • Build custom skills or integrations to assist customers, and document successful processes for future standardization.
  • Tune AI agents by providing the appropriate voice, tools, and specific knowledge base required for specific brands.

Qualifications

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.

  • 5 years of experience in software development and testing or launching software products.

  • 3 years of experience with software design/architecture.

  • Experience with Generative AI (GenAI) concepts (e.g., Large Language Model (LLM), multi-modal, large vision models).

Preferred qualifications:

  • Experience with Knowledge Graph, Ontologies.
  • Experience developing with Generative AI and Large Language Models.
  • Familiarity with open-source AI orchestration frameworks (e.g., LangChain, LlamaIndex). Experience with agentic architectures, tool usage, or the Model Context Protocol (MCP).
  • Background in automated evaluation and benchmarking pipelines
  • Ability to quickly understand customer needs in new domains, and form and test hypotheses on technical solutions and evaluations to improve model/agent outcomes to meet needs.
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